Dear Neil
a convenient work-around is the use of Replace, ReplaceAll;
a typical piece of my code looks like this:
(* a1 does rarely change in the notebook *)
a1=0;
(* a2 can take different values in different scenarios, can be used as
fit parameter, etc. *)
case1:={a2->0}
case2:={a2->1}
(* a3 is varied continously, eg. in plots *)
f[a3_]:=a1+a2+a3;
f[1]
f[1]/.case1
Bye
Ben
On 8 Aug., 11:10, Neil Stewart <neil.stew... at warwick.ac.uk> wrote:
> When implementing a mathematical model in physics or psychology, for
> example, how do other people deal with model parameters in Mathematica?
> Would you represent the speed of light as a global variable or a local
> variable. For example, would you use
>
> Energy[m_]:=m*c^2 (* c is a global variable *)
>
> or
>
> Energy[m_,c_]:=m*c^2 (* c is a local variable *)
>
> ?
>
> The first seems neater. But problems arise in psychology, my domain, where
> the values of model parameters are unknown and are left as free parameters,
> adjusted to best-fit the data.
>
> Both local and global methods work well with optimisation. For example,
>
> NMinimize[Energy[1],{c}]
> {0., {c -> 0.}}
>
> and
>
> NMinimize[Energy[1,c],{c}]
> {0., {c -> 0.}}
>
> But the global variable solution does not work well with Manipulate.
> For example,
>
> Manipulate[Dynamic[Energy[1]], {c, 0, 1}, LocalizeVariables -> False]
>
> works, but looks a right mess and also results in c taking a value that
> needs a Clear[c] before using other functions like NMinimize. On the other
> hand the local variable version
>
> Manipulate[Energy[1, c], {c, 0, 1}]
>
> is nice and simple. But the local variable solution results in having to
> pass all of the model parameters to the function. This is fine in this
> trivial example, but becomes unwieldy when there are ten model parameters
> and the model is defined using a set of functions. (A c-like struct could
> help, but there does not seem to be a neat way to do this in Mathematica.)
>
> So what do other people do? I'd be really interested to hear.